The amount of IoT devices deployed worldwide is exploding across all industries and cloud computing is overwhelmed with challenges that prevent IoT from scaling. For this reason, the center of data production and computing is transitioning from the cloud to the edge creating the need of IoT devices with a small but power efficient footprint.

Businesses who fail to focus on demands driven by edge computing will lose their competitive advantage in critical domains like system latency, security, time-to-market and scalability.

nanoAI

From Cloud to Intelligent Edge

Enable your business to scale

nanoAI

nanoAI is a cutting-edge software toolchain developed for rapid development and deployment of efficient machine learning based algorithms for embedded, ultra-low power edge devices.

The toolchain supports various machine learning paradigms from neural networks to probabilistic models with a strong focus on time-series data. nanoAI covers all domains including data acquisition, labelling, algorithm design and deployment to the embedded edge devices.

nanoOS

nanoOS is an embedded software platform written in portable C99 that provides access to highly configurable machine learning algorithms running on the edge. It has a highly abstracted network access, that works with any transport layer such as BLE, Zigbee, NFMI or WiFi, allowing edge devices seamless access to each other within a meshed network.

nanoOS will extend the lifetime value of edge devices as it enables software updates, application configuration, debugging and deployment.

nanoSYSTEMS

This platform is optimized for running the full nanoAI technology suite and serves as the optimal data collection device for intelligent edge machine learning models.

nanoAI Technology

Industry

Reduce the cost of scheduled maintenance and increase equipment lifetime by integrating or retrofitting the nanoAI technology into almost any industrial environment.

nanoAI enabled edge devices help to determine the condition of in-service equipment in order to predict when maintenance should be performed. Detecting anomalies and wear and tear in real-time provides significant cost savings compared to traditional maintenance scheduling because tasks are performed only when needed.

Smart City

The nanoAI technology suite offers very cost-effective, scalable and low-power consumption edge solutions that mitigates the bandwidth and latency constraints related to processing in the Cloud.

nanoAI optimizes the monitoring of the smart city by enabling mesh networks formed by connected devices to react to changing conditions in real-time streamlining movement within the city making it more secure and efficient.

Reduce electricity costs by equipping or retrofitting streetlights with connected nanoAI sensors that enables streetlights to adapt lighting schedules of a specific zones based on movement detection.

Transportation

The nanoAI technology suite attracts businesses within the field of logistics and transportation as it provides building blocks for integrating low-cost IoT devices into your business that can help in creating new business models and gaining the competitive advantage.

Small nanoAI enabled sensors nodes can leverage real-time sensing of cargo and vehicle components allowing for smart asset tracking as well as predicting when next service check should be scheduled to avoid vehicle damages or accidents.

Retail

Security

Health Care

Smart Home

Energy

AI Everywhere

Our vision is to enhance our natural abilities and understanding of our environment, through the evolution of the human relationship, and interaction with technology. A stepping stone towards this vision is nanoAI, which due to its versatility and scalable design can be applied in almost any sector.

nanoAI is a comprehensive ultra-efficient technology suite that enables computing and data analysis on the edge with the lowest memory and processing footprint to date.

nanoAI provides the tools and services needed for any business to scale through IoT by capitalizing on intelligent edge solutions that do not require a host of data scientists, months of implementation time and huge R&D costs to achieve best in class results.

Introducing nanoAI

"The Edge Will Eat The Cloud […] the edge is coming, and it's going to be big."